Scheduling is a basic research problem in both computer science and operations research that seeks to assign resources to operations (e.g., tasks or jobs). The space of problems is vast. Often lists of operations are employed when scheduling operations. For example, a list scheduling dispatcher may assign operations to resources by choosing an executable operation that is closest to a head of a list when processing resources become available.
A number of techniques exist for determining an order of a list of operations that is to be used in a scheduling context. These techniques first determine a cost for each operation and then sort the operations by the determined cost. Specific techniques for determining the costs of operations include regression trees, model trees, linear regression, and nearest neighbor algorithms. Typically, the determined costs for these techniques are predicted operation execution times. Often, the determination of costs is error-prone resulting in under-estimation and over-estimation of costs to varying degrees.
An alternative to determining a list of operations is to categorize operations into broad classifications. For example, a technique used for scheduling computer processing operations is to divide operations into high cost operations and low cost operations by identifying a threshold that divides the high and low cost operations. Such a technique fails to take advantage of ordering operations into a list and the associated benefits of using the list in scheduling.